Pandas Profiling Report

Dataset statistics

Number of variables	9
Number of observations	768
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	54.1 KiB
Average record size in memory	72.2 B

Variable types

NUM	8
BOOL	1

Warnings

`Pregnancies` has 111 (14.5%) zeros	Zeros
`BloodPressure` has 35 (4.6%) zeros	Zeros
`SkinThickness` has 227 (29.6%) zeros	Zeros
`Insulin` has 374 (48.7%) zeros	Zeros
`BMI` has 11 (1.4%) zeros	Zeros

Reproduction

Analysis started	2020-12-12 05:17:18.116220
Analysis finished	2020-12-12 05:19:33.128355
Duration	2 minutes and 15.01 seconds
Software version	pandas-profiling v2.9.0
Download configuration	config.yaml

Pregnancies
Real number (ℝ_≥0)

ZEROS

Distinct	17
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.845052083
Minimum	0
Maximum	17
Zeros	111
Zeros (%)	14.5%
Memory size	6.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	3
Q3	6
95-th percentile	10
Maximum	17
Range	17
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.369578063
Coefficient of variation (CV)	0.8763413316
Kurtosis	0.1592197775
Mean	3.845052083
Median Absolute Deviation (MAD)	2
Skewness	0.9016739792
Sum	2953
Variance	11.35405632
Monotocity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
1	135	17.6%
0	111	14.5%
2	103	13.4%
3	75	9.8%
4	68	8.9%
5	57	7.4%
6	50	6.5%
7	45	5.9%
8	38	4.9%
9	28	3.6%
Other values (7)	58	7.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	111	14.5%
1	135	17.6%
2	103	13.4%
3	75	9.8%
4	68	8.9%

Value	Count	Frequency (%)
17	1	0.1%
15	1	0.1%
14	2	0.3%
13	10	1.3%
12	9	1.2%

Glucose
Real number (ℝ_≥0)

Distinct	136
Distinct (%)	17.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	120.8945312
Minimum	0
Maximum	199
Zeros	5
Zeros (%)	0.7%
Memory size	6.0 KiB

Quantile statistics

Minimum	0
5-th percentile	79
Q1	99
median	117
Q3	140.25
95-th percentile	181
Maximum	199
Range	199
Interquartile range (IQR)	41.25

Descriptive statistics

Standard deviation	31.9726182
Coefficient of variation (CV)	0.2644670347
Kurtosis	0.6407798204
Mean	120.8945312
Median Absolute Deviation (MAD)	20
Skewness	0.1737535018
Sum	92847
Variance	1022.248314
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	17	2.2%
99	17	2.2%
129	14	1.8%
125	14	1.8%
111	14	1.8%
106	14	1.8%
95	13	1.7%
108	13	1.7%
105	13	1.7%
102	13	1.7%
Other values (126)	626	81.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5	0.7%
44	1	0.1%
56	1	0.1%
57	2	0.3%
61	1	0.1%

Value	Count	Frequency (%)
199	1	0.1%
198	1	0.1%
197	4	0.5%
196	3	0.4%
195	2	0.3%

BloodPressure
Real number (ℝ_≥0)

ZEROS

Distinct	47
Distinct (%)	6.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	69.10546875
Minimum	0
Maximum	122
Zeros	35
Zeros (%)	4.6%
Memory size	6.0 KiB

Quantile statistics

Minimum	0
5-th percentile	38.7
Q1	62
median	72
Q3	80
95-th percentile	90
Maximum	122
Range	122
Interquartile range (IQR)	18

Descriptive statistics

Standard deviation	19.35580717
Coefficient of variation (CV)	0.2800908166
Kurtosis	5.18015656
Mean	69.10546875
Median Absolute Deviation (MAD)	8
Skewness	-1.843607983
Sum	53073
Variance	374.6472712
Monotocity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
70	57	7.4%
74	52	6.8%
68	45	5.9%
78	45	5.9%
72	44	5.7%
64	43	5.6%
80	40	5.2%
76	39	5.1%
60	37	4.8%
0	35	4.6%
Other values (37)	331	43.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	35	4.6%
24	1	0.1%
30	2	0.3%
38	1	0.1%
40	1	0.1%

Value	Count	Frequency (%)
122	1	0.1%
114	1	0.1%
110	3	0.4%
108	2	0.3%
106	3	0.4%

SkinThickness
Real number (ℝ_≥0)

ZEROS

Distinct	51
Distinct (%)	6.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	20.53645833
Minimum	0
Maximum	99
Zeros	227
Zeros (%)	29.6%
Memory size	6.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	23
Q3	32
95-th percentile	44
Maximum	99
Range	99
Interquartile range (IQR)	32

Descriptive statistics

Standard deviation	15.95221757
Coefficient of variation (CV)	0.776775494
Kurtosis	-0.5200718662
Mean	20.53645833
Median Absolute Deviation (MAD)	12
Skewness	0.1093724965
Sum	15772
Variance	254.4732453
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	227	29.6%
32	31	4.0%
30	27	3.5%
27	23	3.0%
23	22	2.9%
33	20	2.6%
18	20	2.6%
28	20	2.6%
31	19	2.5%
39	18	2.3%
Other values (41)	341	44.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	227	29.6%
7	2	0.3%
8	2	0.3%
10	5	0.7%
11	6	0.8%

Value	Count	Frequency (%)
99	1	0.1%
63	1	0.1%
60	1	0.1%
56	1	0.1%
54	2	0.3%

Insulin
Real number (ℝ_≥0)

ZEROS

Distinct	186
Distinct (%)	24.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	79.79947917
Minimum	0
Maximum	846
Zeros	374
Zeros (%)	48.7%
Memory size	6.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	30.5
Q3	127.25
95-th percentile	293
Maximum	846
Range	846
Interquartile range (IQR)	127.25

Descriptive statistics

Standard deviation	115.2440024
Coefficient of variation (CV)	1.444169856
Kurtosis	7.214259554
Mean	79.79947917
Median Absolute Deviation (MAD)	30.5
Skewness	2.272250858
Sum	61286
Variance	13281.18008
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	374	48.7%
105	11	1.4%
140	9	1.2%
130	9	1.2%
120	8	1.0%
100	7	0.9%
94	7	0.9%
180	7	0.9%
110	6	0.8%
115	6	0.8%
Other values (176)	324	42.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	374	48.7%
14	1	0.1%
15	1	0.1%
16	1	0.1%
18	2	0.3%

Value	Count	Frequency (%)
846	1	0.1%
744	1	0.1%
680	1	0.1%
600	1	0.1%
579	1	0.1%

BMI
Real number (ℝ_≥0)

ZEROS

Distinct	248
Distinct (%)	32.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	31.99257812
Minimum	0
Maximum	67.1
Zeros	11
Zeros (%)	1.4%
Memory size	6.0 KiB

Quantile statistics

Minimum	0
5-th percentile	21.8
Q1	27.3
median	32
Q3	36.6
95-th percentile	44.395
Maximum	67.1
Range	67.1
Interquartile range (IQR)	9.3

Descriptive statistics

Standard deviation	7.88416032
Coefficient of variation (CV)	0.2464371671
Kurtosis	3.290442901
Mean	31.99257812
Median Absolute Deviation (MAD)	4.6
Skewness	-0.4289815885
Sum	24570.3
Variance	62.15998396
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
32	13	1.7%
31.6	12	1.6%
31.2	12	1.6%
0	11	1.4%
33.3	10	1.3%
32.4	10	1.3%
32.8	9	1.2%
30.8	9	1.2%
32.9	9	1.2%
30.1	9	1.2%
Other values (238)	664	86.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11	1.4%
18.2	3	0.4%
18.4	1	0.1%
19.1	1	0.1%
19.3	1	0.1%

Value	Count	Frequency (%)
67.1	1	0.1%
59.4	1	0.1%
57.3	1	0.1%
55	1	0.1%
53.2	1	0.1%

DiabetesPedigreeFunction
Real number (ℝ_≥0)

Distinct	517
Distinct (%)	67.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.4718763021
Minimum	0.078
Maximum	2.42
Zeros	0
Zeros (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	0.078
5-th percentile	0.14035
Q1	0.24375
median	0.3725
Q3	0.62625
95-th percentile	1.13285
Maximum	2.42
Range	2.342
Interquartile range (IQR)	0.3825

Descriptive statistics

Standard deviation	0.331328595
Coefficient of variation (CV)	0.7021513764
Kurtosis	5.594953528
Mean	0.4718763021
Median Absolute Deviation (MAD)	0.1675
Skewness	1.919911066
Sum	362.401
Variance	0.1097786379
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.254	6	0.8%
0.258	6	0.8%
0.259	5	0.7%
0.238	5	0.7%
0.207	5	0.7%
0.268	5	0.7%
0.261	5	0.7%
0.167	4	0.5%
0.19	4	0.5%
0.27	4	0.5%
Other values (507)	719	93.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.078	1	0.1%
0.084	1	0.1%
0.085	2	0.3%
0.088	2	0.3%
0.089	1	0.1%

Value	Count	Frequency (%)
2.42	1	0.1%
2.329	1	0.1%
2.288	1	0.1%
2.137	1	0.1%
1.893	1	0.1%

Age
Real number (ℝ_≥0)

Distinct	52
Distinct (%)	6.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	33.24088542
Minimum	21
Maximum	81
Zeros	0
Zeros (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	21
5-th percentile	21
Q1	24
median	29
Q3	41
95-th percentile	58
Maximum	81
Range	60
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	11.76023154
Coefficient of variation (CV)	0.3537881556
Kurtosis	0.6431588885
Mean	33.24088542
Median Absolute Deviation (MAD)	7
Skewness	1.129596701
Sum	25529
Variance	138.3030459
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22	72	9.4%
21	63	8.2%
25	48	6.2%
24	46	6.0%
23	38	4.9%
28	35	4.6%
26	33	4.3%
27	32	4.2%
29	29	3.8%
31	24	3.1%
Other values (42)	348	45.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
21	63	8.2%
22	72	9.4%
23	38	4.9%
24	46	6.0%
25	48	6.2%

Value	Count	Frequency (%)
81	1	0.1%
72	1	0.1%
70	1	0.1%
69	2	0.3%
68	1	0.1%

Outcome
Boolean

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

0	500
1	268

Common Values
Chart

Value	Count	Frequency (%)
0	500	65.1%
1	268	34.9%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

First rows

	Pregnancies	Glucose	BloodPressure	SkinThickness	Insulin	BMI	DiabetesPedigreeFunction	Age	Outcome
0	6	148	72	35	0	33.6	0.627	50	1
1	1	85	66	29	0	26.6	0.351	31	0
2	8	183	64	0	0	23.3	0.672	32	1
3	1	89	66	23	94	28.1	0.167	21	0
4	0	137	40	35	168	43.1	2.288	33	1
5	5	116	74	0	0	25.6	0.201	30	0
6	3	78	50	32	88	31.0	0.248	26	1
7	10	115	0	0	0	35.3	0.134	29	0
8	2	197	70	45	543	30.5	0.158	53	1
9	8	125	96	0	0	0.0	0.232	54	1

Last rows

	Pregnancies	Glucose	BloodPressure	SkinThickness	Insulin	BMI	DiabetesPedigreeFunction	Age	Outcome
758	1	106	76	0	0	37.5	0.197	26	0
759	6	190	92	0	0	35.5	0.278	66	1
760	2	88	58	26	16	28.4	0.766	22	0
761	9	170	74	31	0	44.0	0.403	43	1
762	9	89	62	0	0	22.5	0.142	33	0
763	10	101	76	48	180	32.9	0.171	63	0
764	2	122	70	27	0	36.8	0.340	27	0
765	5	121	72	23	112	26.2	0.245	30	0
766	1	126	60	0	0	30.1	0.349	47	1
767	1	93	70	31	0	30.4	0.315	23	0

Overview

Variables

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Missing values

Sample

First rows

Last rows